Nature Inspired Search and Optimisation

Level 3/H

Outline

Natural Computation is the study of computational systems that use ideas and get inspiration from a variety of natural systems. Its powerful techniques can be applied not only to optimisation but also learning and design. Many such techniques can be characterised as general randomised search heuristics which are the method of choice in practical optimisation scenarios where no good problem-specific algorithms are available.Topics covered in this module focus on nature-inspired optimisation techniques. Where appropriate, the methods discussed are related to other approaches and application areas. Example topics covered include variants of local search, evolutionary computation, swarm intelligence and artificial immune systems. While the focus is on the applications of such techniques, theoretical foundations are also briefly studied.

Aims

The aims of this module are to:

introduce the main concepts, techniques and applications in the field of randomised search heuristics and nature-inspired computing with a focus on (but not limited to) optimisation

give students some experience on when such techniques are useful and how to use them in practice

Learning Outcomes

On successful completion of this module, the student should be able to:

Describe different nature-inspired search and optimisation methods and explain how they are applied to solve real world problems

Discuss relations, similarities and differences between the most important heuristics and nature-inspired algorithms presented in the module and other search and optimisation techniques